![Man in blue button down shirt poses outside for a picture with his arms crossed.](/sites/default/files/styles/featured_square_large/public/2024-07/Troy_Carter_headshot.jpeg?h=8a7fc05e&itok=VFmZIzHo)
Filter News
Area of Research
- Biological Systems (1)
- Biology and Environment (34)
- Clean Energy (19)
- Computational Biology (1)
- Computer Science (1)
- Fusion and Fission (4)
- Materials (6)
- Materials for Computing (2)
- National Security (10)
- Neutron Science (8)
- Nuclear Science and Technology (6)
- Quantum information Science (1)
- Supercomputing (28)
News Type
News Topics
- (-) Advanced Reactors (8)
- (-) Bioenergy (51)
- (-) Composites (6)
- (-) Coronavirus (17)
- (-) Fossil Energy (4)
- (-) Frontier (24)
- (-) Machine Learning (22)
- (-) Molten Salt (1)
- 3-D Printing/Advanced Manufacturing (39)
- Artificial Intelligence (46)
- Big Data (24)
- Biology (59)
- Biomedical (28)
- Biotechnology (11)
- Buildings (19)
- Chemical Sciences (24)
- Clean Water (14)
- Climate Change (50)
- Computer Science (83)
- Critical Materials (2)
- Cybersecurity (14)
- Decarbonization (46)
- Education (1)
- Emergency (2)
- Energy Storage (29)
- Environment (104)
- Exascale Computing (25)
- Fusion (31)
- Grid (23)
- High-Performance Computing (44)
- Hydropower (5)
- Isotopes (27)
- ITER (2)
- Materials (43)
- Materials Science (45)
- Mathematics (7)
- Mercury (7)
- Microelectronics (2)
- Microscopy (20)
- Nanotechnology (16)
- National Security (37)
- Net Zero (8)
- Neutron Science (47)
- Nuclear Energy (55)
- Partnerships (16)
- Physics (28)
- Polymers (8)
- Quantum Computing (20)
- Quantum Science (30)
- Renewable Energy (1)
- Security (11)
- Simulation (31)
- Software (1)
- Space Exploration (12)
- Statistics (1)
- Summit (30)
- Sustainable Energy (44)
- Transformational Challenge Reactor (3)
- Transportation (27)
Media Contacts
![ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/2022-G00330_KESER%20Illustration_0.jpg?h=1cb48fc4&itok=c6ZuDdDg)
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
![Earth Day](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Earth%20image.png?h=8f74817f&itok=5rQ_su9Z)
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
![ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Nucleic%20Cover%20Illustration.jpg?h=4a9d1e17&itok=iw81emAt)
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
![Scientists with the Center for Bioenergy Innovation at ORNL highlighted a hybrid approach that uses microbes and catalysis to convert cellulosic biomass into fuels suitable for aviation and other difficult-to-electrify sectors. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-03/AirplaneSwitchgrass_0.png?h=198a5201&itok=Vuu-Rrk7)
The rapid pace of global climate change has added urgency to developing technologies that reduce the carbon footprint of transportation technologies, especially in sectors that are difficult to electrify.
![Melissa Cregger](/sites/default/files/styles/list_page_thumbnail/public/2022-03/Cregger%202021-P03021.jpg?h=c6980913&itok=uistMm4e)
The Center for Bioenergy Innovation at ORNL offers a unique opportunity for early career scientists to conduct groundbreaking research while learning what it takes to manage a large collaborative science center.
![Bryan Piatkowski is a Liane Russell Distinguished Fellow at ORNL developing a framework to better understand the genetic underpinnings of desirable plant traits so they may be used to create climate-resilient crops for food, bioenergy and carbon sequestration. Credit: Carlos Jones/ORNL, U.S. Dept of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2022-03/Piatkowski%20outdoors%202021-P06111_0.jpg?h=c6980913&itok=bhUc5-NN)
Bryan Piatkowski, a Liane Russell Distinguished Fellow in the Biosciences Division at ORNL, is exploring the genetic pathways for traits such as stress tolerance in several plant species important for carbon sequestration
![Chunliu Zhuo is a postdoctoral researcher at the University of North Texas BioDiscovery Institute. Credit: University of North Texas](/sites/default/files/styles/list_page_thumbnail/public/2022-03/20_0302_Dixon-and-Zhuo15.png?h=a49d782d&itok=K0GDwbRk)
A team of researchers working within the Center for Bioenergy Innovation at ORNL has discovered a pathway to encourage a type of lignin formation in plants that could make the processing of crops grown for products such as sustainable jet fuels easier and less costly.
![QLAN submit - A team from the U.S. Department of Energy’s Oak Ridge National Laboratory, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL using entangled photons passing through optical fiber. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/QLAN%20submit_0.jpg?h=cd715a88&itok=JV1MjQHH)
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
![An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/sars_cov_2_bk.png?h=05c2797f&itok=jQ2D9aTr)
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
![This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/thermosipho_collabfold2_0.jpg?h=3432ff3c&itok=4xhLbjKZ)
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.